Evolution of Drilling and Completions in the Slave Point to Optimize Economics
Bibliographic record
Abstract
Abstract This paper will detail the technological evolution of drilling and completion practices utilized to optimize economic development of the Slave Point carbonate platform specifically in the Evi and Otter fields in northern Alberta. The Slave Point platform was initially targeted for conventional production via vertical wells in the early 1980s. Success was marginal due to the unpredictability of localized porosity development. As a result, full scale commercial development of this resource was deemed uneconomic due to poor reservoir quality. More recently, however, horizontal drilling and multistage fracturing technology has allowed operators to open up lower porosity horizons to improve flow capacity, improve recoveries, and allow for commercial development from zones previously deemed as uneconomic. The Slave Point has a greater thickness and is less permeable than other tight rock plays in Alberta such as the Cardium and Viking. It produces high-quality, light oil with low water and solution gas production rates. Despite high estimates of original oil in place of approximately 3 to 10 MMbbl per section, horizontal well rates are still challenged due to lower permeability through the pay section. In this regard, the continued deployment of innovation and technology has been critical in improving well production performance, compressing project costs, and ultimately optimizing project economics. The focus of this paper is solely upon one of the major Slave Point operators who has drilled 49 horizontal wells accounting for 200,000 m (656,000 ft) drilled and 1,350 fracture stages in the Evi and Otter Slave Point fields since 2008. This operator has continually deployed advancing technologies to improve project economics. The information will be presented in terms of the influence of technology on well design, the optimization and deployment of the various technologies, and the demonstrated improvement on productivity and reserve recovery. The discussion will focus on three development phases outlined below, which highlight the progression from vertical to horizontal technology. Vertical AppraisalSingle Lateral DevelopmentDual Lateral Development The case studies presented will clearly demonstrate the production impact upon the utilization and application of these technologies. The methods and lessons learned through the use of dual laterals, open hole junctures and open hole multistage systems can be applied to other unconventional formations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".